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Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks

文献类型：期刊论文

作者Yang, Chenguang5; Peng, Guangzhu2; Cheng, Long3,4; Na, Jing6; Li, Zhijun1
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
出版日期2021-05-01
卷号51期号:5页码:3282-3292
关键词Robot sensing systems Force Robot kinematics Artificial neural networks Admittance Torque Admittance control error transformation force observer Kinect neural adaptive control neural networks (NNs) robot
ISSN号2168-2216
DOI10.1109/TSMC.2019.2920870
通讯作者Yang, Chenguang(cyang@ieee.org)
英文摘要In this paper, a force sensorless control scheme based on neural networks (NNs) is developed for interaction between robot manipulators and human arms in physical collision. In this scheme, the trajectory is generated by using geometry vector method with Kinect sensor. To comply with the external torque from the environment, this paper presents a sensorless admittance control approach in joint space based on an observer approach, which is used to estimate external torques applied by the operator. To deal with the tracking problem of the uncertain manipulator, an adaptive controller combined with the radial basis function NN (RBFNN) is designed. The RBFNN is used to compensate for uncertainties in the system. In order to achieve the prescribed tracking precision, an error transformation algorithm is integrated into the controller. The Lyapunov functions are used to analyze the stability of the control system. The experiments on the Baxter robot are carried out to demonstrate the effectiveness and correctness of the proposed control scheme.
资助项目Engineering and Physical Sciences Research Council[EP/S001913] ; National Natural Science Foundation of China[61873268] ; National Natural Science Foundation of China[61633016] ; Beijing Municipal Natural Science Foundation[L182060]
WOS研究方向Automation & Control Systems ; Computer Science
语种英语
WOS记录号WOS:000640749000055
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构Engineering and Physical Sciences Research Council ; National Natural Science Foundation of China ; Beijing Municipal Natural Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/44337]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Yang, Chenguang
作者单位1.Univ Sci & Technol China, Dept Automat, Hefei 230026, Peoples R China
2.Univ Macau, Fac Sci & Technol, Dept Comp & Informat Sci, Macau 999078, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
5.Univ West England, Bristol Robot Lab, Bristol BS16 1QY, Avon, England
6.Kunming Univ Sci & Technol, Fac Mech & Elect Engn, Kunming 650500, Yunnan, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Chenguang,Peng, Guangzhu,Cheng, Long,et al. Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021,51(5):3282-3292.
APA Yang, Chenguang,Peng, Guangzhu,Cheng, Long,Na, Jing,&Li, Zhijun.(2021).Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,51(5),3282-3292.
MLA Yang, Chenguang,et al."Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 51.5(2021):3282-3292.

入库方式： OAI收割

来源：自动化研究所

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